Abstract
The need to develop smart unmanned aerial vehicles (UAVs) which are capable of deciding their trajectories is increasing at a rapid pace. Due to their usage in wide range of applications, such as-military, security, communications, survey mapping, disaster management, etc., the provisioning of end-to-end quality of service (QoS) is a challenging task in UAV environment. Moreover, with limited power, the efficiency of the UAVs can be enhanced if adaptive decisions with respect to their itineraries is considered dynamically. However, most of the solutions reported in the literature are not efficient with respect to QoS preservations for various applications. Motivated by this, several recently proposed meta-heuristic optimization schemes for reactive path planning of UAVs have been explored while designing a UAV path planning problem using multiverse optimizer (MVO). By carrying out the simulations over 1000 iterations, it has been demonstrated that MVO algorithm performs better in majority of the cases with average fitness function value of 0.152 and average execution time of 33.686 s.